, e.g., irregular missing patterns, interdependent logical constraints, data anomalies etc. Our model selection procedure …

This paper presents recent developments in model selection and model averaging for parametric and nonparametric models …. While there is extensive literature on model selection under parametric settings, we present recently developed results in … misleading confidence intervals. Thus an alternative to model selection is model averaging where the estimated model is the …

This paper develops model selection and averaging methods for moment restriction models. We first propose a focused …

contemporaneous effects combined with an automatic general-to-specific model selection. The resulting parsimonious structural vector …

institutional interdependencies by applying a model selection approach which is innovative within this literature. In doing so, we …

suggest that the performance of the model selection methods depends on sample size and stochastic variance. The Bootstrap … the model selection methods to identify the true asymmetric price relationship decreases with increase in stochastic …

, e.g., irregular missing patterns, interdependent logical constraints, data anomalies etc. Our model selection procedure …

model selection criteria to compare our trigonometric trend model with Slade��s (1982) quadratic trend model, as …

of data series. Model selection aims to identify the best method of forecasting for an individual series within the data … set. Various selection rules have been proposed in order to enhance forecasting accuracy. In theory, model selection is … circumstances under which model selection is beneficial. Three measures are examined for characterising the data series, namely …

simulations indicate that model selection performance depends on bootstrap sample size and the amount of noise in the data …